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digital transformation for tourism
04Apr

Digital Transformation for Tourism

The digital revolution is in full swing, with individuals and businesses increasingly interacting through social networks and digital devices. In this new era, consumers have grown more discerning, leveraging mobile technology to make informed decisions about products, services, and trusted providers. As mobile apps become integral to daily life, organizations are compelled to reinvent their customer value propositions and operating models through digital transformation to remain competitive in today’s market. Digital transformation has become a critical priority across industries, with the tourism sector standing out as a prime example of significant disruption driven by digital technologies. According to McKinsey & Company, the tourism industry has been undergoing a digital revolution for over a decade, transforming how travelers plan, book, and experience their trips. This shift has led to changing consumer behaviors, with travelers now demanding more personalized and seamless experiences. The push toward digital adoption in tourism is accelerating. A Skift survey found that 83% of respondents view digital transformation as a top priority. Tourism businesses are increasingly investing in technology to enhance customer experiences, optimize operations, and drive revenue growth. To boost enterprise agility, companies must make strategic decisions across five key dimensions of their operating models: One of the most notable impacts of digital transformation is the revolution in the booking process. Travelport Digital estimates that over 700 million people will book trips online by 2023, marking a 15% increase from previous years. Key statistics highlight this global shift in traveler preferences: Mobile apps have become essential tools for travelers, enabling them to research, plan, and book trips seamlessly. In the hospitality and tourism sector, key digital transformation trends include: Emerging technologies like cognitive computing, omnichannel models, and advanced personalization are further reshaping the future of the industry. Artificial intelligence (AI) and machine learning are increasingly used to tailor travel experiences based on consumer preferences and behaviors, as noted by GlobalData. AI also improves operational efficiency, with chatbots handling customer inquiries effectively. Augmented reality (AR) and virtual reality (VR) are enhancing customer experiences by allowing travelers to explore destinations virtually before booking. Meanwhile, social media continues to play a pivotal role in promoting tourism businesses and reaching new audiences. In conclusion, digital transformation is no longer optional for tourism businesses—it is a necessity to remain competitive. The adoption of digital technologies has fundamentally reshaped the travel experience, and businesses must embrace this evolution to meet changing consumer expectations and maintain relevance in an increasingly digital world. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 4, 2025in Artificial Intelligence, Data, Enterprise, Google, Salesforce, Technology

Get a Grip on Agentforce

Salesforce Agentforce: The Next Evolution in AI Automation Salesforce is a powerhouse for sales, customer support, and marketing. While automations and integrations already help streamline workflows, Salesforce Agentforce takes efficiency to a whole new level. This guide breaks down what Agentforce is, how it works, and five impactful ways to use it in your organization. What is Salesforce Agentforce? Agentforce is Salesforce’s AI-driven automation tool that enables businesses to deploy autonomous AI agents for tasks like managing customer requests, scheduling meetings, and optimizing sales pipelines. Unlike basic chatbots, these AI agents operate independently—analyzing data, making decisions, and executing actions without constant user input. How AI Agents Work Traditional AI tools like ChatGPT and Jasper assist with tasks when prompted, but AI agents go further. They: With Agentforce, Salesforce users can automate more than ever before—including delegating routine decisions to AI. 5 Ways to Use Salesforce Agentforce 1. Enhancing Customer Support with AI Agents AI agents go beyond standard chatbots by dynamically searching company data in real time to provide personalized support. They can: 2. Automating Routine Support Tasks Many customer requests are too complex for basic automation but still repetitive for human agents. AI agents can independently process requests like: ✔ Updating reservations (restaurants, hotels, events)✔ Redeeming loyalty points (e-commerce, retail)✔ Processing refunds (subscriptions, software)✔ Rescheduling appointments (professional services, healthcare) 3. Delivering Smarter, Data-Driven Sales Engagement AI agents can identify opportunities for engagement based on real-time customer data. Instead of waiting for reps to manually review accounts, AI agents can: 4. Launching Workflows Directly from Chat Apps Sales and project teams often brainstorm in chat apps like Slack. Instead of manually transferring ideas into Salesforce, Agentforce can: 5. Scaling Sales Training with AI Sales training is essential but resource-intensive. AI agents can roleplay as prospects, allowing reps to: Take Your AI Automation to the Next Level With Salesforce Agentforce, businesses can go beyond basic automation and deploy intelligent AI agents that handle repetitive tasks, optimize workflows, and drive better customer experiences. FAQ: Salesforce Agentforce What makes Agentforce different from regular automation?Unlike traditional automation, Agentforce AI agents can act independently—analyzing data, making decisions, and executing workflows without human intervention. Is Agentforce the same as Microsoft Copilot?No. While both use AI, Agentforce deploys autonomous AI agents that complete tasks, while Copilot assists users in real time with insights and recommendations. Who should use Agentforce?Salesforce admins, sales teams, and customer support leaders who want to automate complex workflows and free up their teams for high-value tasks. Looking to supercharge your Salesforce automation? Start with Agentforce today. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 3, 2025in AI Tools, Data, Salesforce
AI Agents as Tools of Trust
03Apr

5 Attributes of Agents

Salesforce predicts you will have deployed over 100 AI Agents by the end of the year. What are they? What do they do? Why do you need them? Let’s explore the 5 key attributes of AI Agents. What Is an AI Agent? An AI agent is an intelligent software system that uses artificial intelligence to autonomously pursue goals and complete tasks on behalf of users. Unlike traditional programs, AI agents exhibit reasoning, planning, memory, and decision-making abilities, allowing them to learn, adapt, and operate with minimal human intervention. These agents leverage generative AI and foundation models to process multimodal inputs—such as text, voice, video, and code—enabling them to:✔ Understand and analyze information✔ Make logical decisions✔ Learn from interactions✔ Collaborate with other agents✔ Automate complex workflows From customer service bots to autonomous research assistants, AI agents are transforming industries by handling tasks that once required human intelligence. Key Features of an AI Agent Modern AI agents go beyond simple automation—they possess advanced cognitive and interactive capabilities: Feature Description Reasoning Uses logic to analyze data, solve problems, and make decisions. Acting Executes tasks—whether digital (sending messages, updating databases) or physical (controlling robots). Observing Gathers real-time data via sensors, NLP, or computer vision to understand its environment. Planning Strategizes steps to achieve goals, anticipating obstacles and optimizing actions. Collaborating Works with humans or other AI agents to accomplish shared objectives. Self-Refining Continuously improves through machine learning and feedback. AI Agents vs. AI Assistants vs. Bots While all three automate tasks, they differ in autonomy, complexity, and learning ability: Aspect AI Agent AI Assistant Bot Purpose Autonomously performs complex tasks. Assists users with guided interactions. Follows pre-set rules for simple tasks. Autonomy High—makes independent decisions. Medium—requires user input. Low—limited to scripted responses. Learning Adapts and improves over time. May learn from interactions. Minimal or no learning. Interaction Proactive and goal-driven. Reactive (responds to user requests). Trigger-based (e.g., chatbots). Example: How Do AI Agents Work? AI agents operate through a structured framework: Types of AI Agents AI agents can be classified based on interaction style and collaboration level: 1. By Interaction 2. By Number of Agents Benefits of AI Agents ✅ 24/7 Automation – Handles repetitive tasks without fatigue.✅ Enhanced Decision-Making – Analyzes vast data for insights.✅ Scalability – Manages workflows across industries.✅ Continuous Learning – Improves performance over time. The Future of AI Agents As AI advances, agents will become more autonomous, intuitive, and integrated into daily workflows—from healthcare diagnostics to smart city management. Want to see AI agents in action? Explore 300+ real-world AI use cases from leading organizations. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 3, 2025in Artificial Intelligence, Data, Generative AI, Salesforce
Salesforce and Healthcare
02Apr

Aligning Payers and Providers for True Patient-Centered Care

Patient-centered care is an approach to healthcare that prioritizes the patient’s needs, values, and preferences. It involves treating patients with respect, dignity, and compassion, and ensuring that they are actively involved in their own healthcare decisions. Key Principles of Patient-Centered Care: Benefits of Patient-Centered Care: Improved patient satisfaction and adherence to treatment plans, Enhanced health outcomes, Reduced healthcare costs, and Stronger patient-provider relationships. Examples of Patient-Centered Care: Patient-centered care is a holistic approach to healthcare that focuses on the patient as an individual. By empowering patients and respecting their needs, it aims to improve their health and overall well-being. The Shared Vision vs. Systemic Barriers All healthcare stakeholders agree on one fundamental principle: care should revolve around patients’ needs and preferences. Yet despite this shared goal, competing priorities between payers and providers often create friction that undermines patient-centered care delivery. Theresa Dreyer of the Health Care Transformation Task Force observes: “Payers and providers both want patients to receive accessible, appropriate care. But the current system’s structure frequently puts these groups at odds.” Defining Patient-Centered Care At its core, patient-centered care means: “Imagine the care you’d want for your own family members,” Dreyer suggests. “That’s the standard we should apply across healthcare.” The Fee-for-Service Roadblock The dominant fee-for-service (FFS) model creates inherent conflicts: “FFS turns cost containment into a zero-sum negotiation,” Dreyer explains. “Value-based models offer a collaborative alternative.” Value-Based Care as the Unifying Framework 1. Quality-Focused Contracting 2. Streamlined Prior Authorization 3. Holistic Care Integration The Preventive Care Imperative The long-term nature of prevention creates systemic challenges: “Diabetes management today prevents kidney failure tomorrow,” Dreyer notes. “We need payment models that reward this foresight.” Building Collaborative Solutions For Payers: For Providers: Joint Opportunities: The Path Forward The healthcare industry stands at an inflection point. By embracing value-based models that: Payers and providers can transform their relationship from adversarial to collaborative—with patients as the ultimate beneficiaries. As Dreyer concludes: “Beyond the contracting details and quality metrics, we must remember our shared purpose: helping people achieve and maintain health. When we center that mission, the rest follows.” Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 2, 2025in Life Sciences Cloud, Salesforce, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Managed Services
ai model race
01Apr

AI Model Race Intensifies

AI Model Race Intensifies as OpenAI, Google, and DeepSeek Roll Out New Releases The generative AI competition is heating up as major players like OpenAI, Google, and DeepSeek rapidly release upgraded models. However, enterprises are shifting focus from incremental model improvements to agentic AI—systems that autonomously perform complex tasks. Three Major Releases in 24 Hours This week saw a flurry of AI advancements: Competition Over Innovation? While the rapid releases highlight the breakneck pace of AI development, some analysts see diminishing differentiation between models. The Future: Agentic AI & Real-World Use Cases As model fatigue sets in, businesses are focusing on domain-specific AI applications that deliver measurable ROI. The AI race continues, but the real winners will be those who translate cutting-edge models into practical, agent-driven solutions. Key Takeaways:✔ DeepSeek’s open-source V3 pressures rivals to embrace transparency.✔ GPT-4o’s hyper-realistic images raise deepfake concerns.✔ Gemini 2.5 focuses on structured reasoning for complex tasks.✔ Agentic AI, not just model upgrades, is the next enterprise priority. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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April 1, 2025in Agentic AI, Enterprise, Generative AI, Google
AI Agents Are About to Disrupt Your Marketing Channels
01Apr

AI Agents Are About to Disrupt Your Marketing Channels

AI Agents Are About to Disrupt Your Marketing Channels—Here’s How to Adapt The Future of Marketing Isn’t Human-Centric—It’s Agent-Driven AI agents are poised to revolutionize how brands and consumers interact. These autonomous systems don’t just assist—they research, decide, and transact on behalf of users, fundamentally altering the role of traditional marketing channels. Google knows this. That’s why it’s replacing traditional search with Gemini, an AI agent that delivers answers, not just links. Meta is integrating AI across WhatsApp and Messenger, enabling two-way, large-scale brand interactions. Soon, every channel—email, social, loyalty programs, even your website—will become an AI-powered research and transaction hub. The question isn’t if this will impact your marketing strategy—it’s how soon. What Are AI Agents—And Why Should Marketers Care? AI agents are the next evolution of autonomous AI, combining:✅ Generative AI (content creation, personalization)✅ Predictive AI (data-driven decision-making)✅ Complex task execution (end-to-end customer journeys) Today’s challenge? Most companies struggle to move from AI experimentation to real-world impact. Agents change that—they bridge the gap between hype and execution, turning AI potential into measurable business results. 3 Ways to Future-Proof Your Channel Strategy 1. Build a Bulletproof Data Foundation (Now) AI agents won’t just use data—they’ll demand it to make decisions for customers. 🔹 Example: A customer asks an agent, “Find me the best CRM for small businesses.”🔹 Without structured data: The agent may overlook your product.🔹 With optimized data: Your CRM appears as a top recommendation, complete with pricing, features, and a seamless sign-up link. Action Step: Audit your product data, pricing, and USPs. Ensure they’re machine-readable and easily accessible to AI-driven platforms. 2. Rethink “Channels” as AI Conversation Hubs Traditional marketing funnels (search → browse → convert) will collapse. Instead: Action Step: Optimize for AI-native experiences—structured FAQs, API-accessible pricing, and instant conversion paths. 3. Prepare for AI-to-AI Negotiation B2B and high-consideration purchases (e.g., SaaS, automotive, real estate) will see AI agents negotiating deals on behalf of users. 🔹 Example: A corporate procurement AI evaluates your software against competitors, automatically requesting discounts or custom terms.🔹 Winners will be brands that enable AI-friendly decision-making (clear pricing, comparison data, instant approvals). Action Step: Develop agent-friendly sales collateral—dynamic pricing tables, competitor comparisons, and API-driven contract automation. The Bottom Line: Adapt or Get Displaced The shift to agent-driven marketing isn’t gradual—it’s exponential. Companies that wait will find themselves invisible to AI intermediaries shaping customer decisions. Your roadmap: The future belongs to marketers who design for AI-first experiences. The time to act is now. “AI agents won’t just change marketing—they’ll redefine it. The brands that win will be those that engineer their systems for machines, not just people.”—Salesforce AI Research, 2024 Ready to future-proof your strategy? Contact Tectonic. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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April 1, 2025in Agentforce Platform, Data, Generative AI, Google, Salesforce, Salesforce Implementation Services, Salesforce Marketing Automation
ai agents
29Mar

AI Agents

What AI Agents Are Available on the Market? Limitations of Operator, Computer Use, and Similar Agents OpenAI Operator can be seen as a semi-autonomous agent, but many users note that it asks too many questions and requires excessive confirmations, even in situations that pose no risk:“Operator is like driving a car with cruise control — occasionally taking your foot off the pedals — but it’s far from full-blown autopilot.” Furthermore, although Operator is technically designed to interact with any website, in reality, it’s far from a universal solution. It works reliably on a predefined set of platforms for tasks like shopping and restaurant reservations (such as Instacart and OpenTable), where its functionality has been tested. But outside of these, its performance is inconsistent — sometimes even generating incorrect or entirely fabricated data. Google’s Project Mariner, which aims to offer similar capabilities within Chrome, remains in closed beta for now. Meanwhile, many are eagerly anticipating a consumer product from Claude, which released the API for its Claude Computer Use agent (built on a slightly different principles) back in October 2024. One thing seems certain, though — it will be even more “cautious” than Operator, meaning it’s unlikely to handle tasks like sending emails or posting on social media on your behalf. Thus, browser-based agents come with at least two key limitations:— they work reliably only on a predefined set of websites;— certain actions are prohibited (for example, allowing an agent to send emails autonomously could create conflicts between its owner and others). Mobile agents face similar constraints. Take Perplexity Assistant, one of the earliest attempts at a “versatile” mobile AI agent — it still supports only a limited range of apps where it can operate on behalf of the user. Deep Research Agents To highlight the contrast, let’s look at AI agents built specifically for deep research. This category has seen a surge in new tools recently, and they deliver significantly better results than standard AI-powered web search. Deep Research tools qualify as AI agents due to their high level of autonomy. At this stage, no truly agentic tool exists that can handle any problem on our behalf — even in a semi-autonomous mode, let alone a fully autonomous one. However, there are highly effective agents within specific domains, such as deep research agents. With that in mind, let’s categorize typical AI applications into several groups (use cases) and tackle the following question for each group. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 29, 2025in Data, Google, Salesforce
Why Domain-Specific AI Models Are Outperforming Generic LLMs in Enterprise Applications
28Mar

Why Domain-Specific AI Models Are Outperforming Generic LLMs in Enterprise Applications

The Rise of Domain-Specific Language Models (DSLMs) Businesses are increasingly turning to smaller, industry-focused generative AI models rather than large language models (LLMs) like GPT-4 or Gemini, according to analysts at the Gartner Tech Growth and Innovation Conference. Domain-specific language models (DSLMs)—trained on niche datasets—deliver higher accuracy, lower costs, and better efficiency for specialized industries than general-purpose LLMs. Key Advantages of DSLMs Over LLMs ✔ Industry-Specific Expertise – Fine-tuned for legal, medical, or financial jargon✔ Lower Training Costs – Smaller datasets mean reduced compute expenses✔ Faster Performance – Optimized for real-time enterprise applications✔ Reduced Hallucinations – More precise outputs due to constrained scope Gartner predicts that over 60% of enterprise generative AI models will be domain-specific by 2028, signaling a major shift away from one-size-fits-all LLMs. Why Businesses Are Shifting to DSLMs 1. Cost Efficiency & Faster Deployment 2. Higher Accuracy for Niche Use Cases 3. Regulatory & Compliance Benefits Real-World DSLM Success Stories 1. Legal Document Automation (IBM & German Courts) 2. Healthcare Diagnostics & Imaging 3. Financial & Compliance Reporting The Future: Multimodal & Industry-Tailored AI Gartner analyst Danielle Casey predicts DSLMs will evolve to support multiple data types (text, images, voice) based on industry needs: “The future of enterprise AI isn’t bigger models—it’s smarter, specialized ones.” Key Takeaways for Businesses 🔹 DSLMs outperform LLMs in accuracy & cost for niche applications🔹 Early adopters (legal, healthcare, finance) are already seeing ROI🔹 Multimodal DSLMs will dominate industry-specific AI by 2028🔹 Regulatory-friendly AI is easier to achieve with domain-focused training Next Steps for Enterprises The shift to smaller, specialized AI is accelerating—businesses that adapt now will gain a competitive edge in efficiency and accuracy. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more Tectonic’s Successful Salesforce Track Record Salesforce Technology Services Integrator – Tectonic has successfully delivered Salesforce in a variety of industries including Public Sector, Hospitality, Manufacturing, Read more

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March 28, 2025in Data, Enterprise, Generative AI
Salesforce Health Cloud
26Mar

How Salesforce Health Cloud’s 360-Degree CRM View Enhances EHR Performance

Salesforce Health Cloud is a powerful Customer Relationship Management (CRM) platform designed for healthcare, offering a comprehensive 360-degree view of patient data. By consolidating medical records, test results, and insurance details from multiple sources, it bridges the gap between clinical and non-clinical information in real time—empowering providers with actionable insights. Recent studies highlight the impact of healthcare CRM solutions: With AI-driven predictive analytics and seamless EHR integration, Salesforce Health Cloud is transforming care coordination. By eliminating data silos, streamlining workflows, and boosting patient engagement, it enhances EHR performance, clinical outcomes, and operational efficiency. In this insight, we explore how Salesforce Health Cloud’s 360-degree CRM view elevates EHR capabilities. Understanding EHRs and Healthcare CRMs What Are EHRs? Electronic Health Records (EHRs) are digital versions of patient charts, providing real-time access to authorized users. Unlike traditional paper records, EHRs enable seamless data sharing across: What Are Healthcare CRMs? Healthcare Customer Relationship Management (CRM) systems focus on patient engagement, care coordination, and experience optimization. Key features include: How a 360-Degree CRM View Boosts EHR Performance 1. Enhanced Data Integration & Visibility A 360-degree CRM view unifies clinical, administrative, financial, and patient interaction data into a single platform. This integration: 2. Optimized Operational Efficiency By integrating CRM data directly into EHRs, healthcare organizations can: 3. Personalized Patient Engagement A holistic CRM view helps providers understand each patient’s: This enables: 4. AI-Powered Actionable Insights Integrating AI and machine learning with a 360-degree CRM view allows: Tectonic’s Salesforce Health Cloud Solution Tectonic delivers customized Salesforce Health Cloud solutions to maximize efficiency, patient outcomes, and workflow optimization. Our expertise includes: ✔ Custom implementation tailored to your organization’s needs✔ Seamless integration with EHRs, billing systems, and patient engagement tools✔ Comprehensive training to empower care teams✔ Ongoing support for updates, performance tuning, and troubleshooting With Tectonic, unlock the full potential of Salesforce Health Cloud—transforming patient care and operational excellence. Ready to enhance your EHR performance? Let’s connect!  Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 26, 2025in Data, Salesforce, Salesforce Health Cloud
21Mar

Salesforce Development Services

Salesforce has become one of the leading platforms to change the business-to-customer relationships and experience. Salesforce development services don’t just offer Salesforce solutions and software implementation; they help you adopt a customized functionality that enriches delivery and profit. Salesforce, by definition, is a powerful platform that enables a business to adopt CRM-driven leads and expansion in the industry. At Tectonic, we believe that a decision to opt for Salesforce services is just the beginning of a battle to beat the competition. This is where Tectonic comes in with custom coding and the finest Salesforce development services; we help you figure out everything from configurations and complications to legacy data systems and more. We are made up of a team of Salesforce experts, development professionals, and years of experience in strategic consulting, planning, integration, implementation, deployment, and delivery of business-changing and success-driven services. Why choose Tectonic’s Salesforce Development services? Tectonic, with its years of expertise and experience in technical services and strategic consulting, has the most efficient and organized set of professionals to help your business understand and embed everything-Salesforce. Tectonic understands innovation and change can be overwhelming and sound too complex, and it is our business to handle that for you while delivering a profitable and growing system that expands your reach in the industry. And remains scalable over time. The industry has moved from traditional on-premises CRM to cloud-based CRM to address scalability, change management, and time-to-market needs of businesses. For companies looking for SaaS offerings on the cloud, Salesforce is an undisputed leader. Also, companies looking to build customized business applications can capitalize on Force.com as a platform as a service (PaaS). Implement innovative Salesforce solutions that streamline your operations, boost your productivity, and drive sustainable growth. Work with our team of certified Salesforce developers who bring extensive experience and in-depth knowledge to every project. At Tectonic we focus on industries where we have expertise to help you get the most impactful Salesforce development. Get customized Salesforce development services from Tectonic designed to meet your unique business needs, ensuring seamless integration and enhanced functionality. Build and deploy scalable Salesforce platforms that adapt as your business grows and evolves, keeping you ahead of the competition. Collaborate with Tectonic to unlock the full potential of Salesforce, where development is turning challenges into opportunities for success. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 21, 2025in Data, Salesforce, Salesforce Development Services
Dementia Care and Telemedicine
21Mar

Dementia Care and Telemedicine

How 3 Health Systems Are Leveraging Telemedicine for Dementia Care Telemedicine is expanding access to dementia care, particularly for rural and elderly patients, though challenges like technology barriers and sustainability remain. Dementia—an umbrella term for cognitive and memory disorders—affects millions of Americans directly and indirectly. By 2060, nearly 1 million people in the U.S. are projected to develop dementia. While no cure exists, the growing prevalence underscores the need for accessible and effective care solutions. Telehealth has emerged as a critical tool in meeting this demand. The rapid adoption of virtual care during the COVID-19 pandemic transformed dementia care delivery. A 2024 study found that telehealth use surged among dementia patients, particularly those with long travel distances to clinics and the oldest age groups. For health systems like the University of Mississippi Medical Center (UMMC), telemedicine has been a game-changer. “COVID-19 changed things almost overnight,” said Dr. Kim Tarver, associate professor of medicine and director of clinical services at UMMC’s MIND Center. “We have patients who travel three hours to see us. Being able to communicate without requiring a clinic visit every time is incredibly helpful.” UMMC is among several health systems integrating telehealth into dementia care, though challenges like technology access and financial sustainability persist. Telehealth’s Role in Dementia Care: Benefits and Applications Dementia care is uniquely suited for telehealth. Virtual visits allow for evaluations, treatment adjustments, and follow-ups while offering privacy and flexibility that in-person visits cannot. At UMMC, clinicians conduct cognitive assessments like the Montreal Cognitive Assessment (MoCA) remotely. A nurse guides patients through the test via screen-sharing, while caregivers assist with physical exam components when needed. “I’ll ask the caregiver to perform parts of the exam, like cerebellar function tests, while I observe via video,” Tarver explained. Though in-person visits are still used for verification, virtual assessments have proven comparably accurate. Telemedicine also enables family members to discuss concerns privately—especially valuable when patients are unaware of or resistant to acknowledging their condition. Extending Dementia Care Through Virtual Workforce Solutions Health systems are also using telehealth to expand their dementia care workforce. At the University of California, San Francisco (UCSF), unlicensed but trained care navigators support families, handling routine assessments and triaging complex cases to specialists. “Navigators manage caseloads of families, consulting licensed experts only when needed,” said Dr. Katherine Possin, a neurology professor at UCSF. “This extends the reach of our limited dementia specialist workforce.” Similarly, Banner Health’s Dementia Care Partners program employs health coaches (Certified Nursing Assistants) to conduct initial assessments and provide ongoing support, reducing clinician workload. “If I train 30 people who each support 3,000 patients, the impact multiplies rapidly,” said Dr. Ganesh Gopalakrishna of Banner Alzheimer’s Institute. Banner also uses Project ECHO, a telehealth-based training model, to educate community providers—from physicians to elder care attorneys—on dementia care best practices. Overcoming Telehealth Challenges in Dementia Care Despite its benefits, implementing telehealth in dementia care presents hurdles: The Future of Telehealth in Dementia Care Despite obstacles, providers see immense value in virtual dementia care—reducing caregiver burden, preventing unnecessary hospitalizations, and improving patients’ quality of life. “I hope telehealth becomes the standard of care,” Possin said. As health systems refine their approaches, telemedicine promises to play an increasingly vital role in dementia care—bridging gaps in access and delivering support to patients and families when they need it most. Tectonic can help you transform telehealth in your organization. Contact us today. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 21, 2025in Life Sciences Cloud, Salesforce, Salesforce Development Services, Salesforce Health and Life Sciences Solutions, Salesforce Health Cloud, Salesforce Implementation Services, Technology
Agentic AI is Here
20Mar

The Catalytic Potential of Agentic AI in Cloud Computing

Artificial intelligence continues to drive a technological flywheel where each breakthrough enables more sophisticated systems. While generative AI has dominated discourse since ChatGPT’s 2022 debut, 2025 appears poised to become the year of agentic AI – marking a paradigm shift from passive information processing toward proactive, autonomous systems capable of executing complex workflows. The Rise of Autonomous AI Agents Unlike conventional chatbots that facilitate human-led interactions, agentic AI systems operate independently to complete multi-step processes. These autonomous agents demonstrate capabilities ranging from specialized functions like sales outreach and travel booking to broader applications in cybersecurity and human resources. Industry analysts anticipate these systems will follow an adoption curve reminiscent of early internet technologies, potentially creating multi-billion dollar markets as they become embedded in daily operations. Cloud infrastructure providers stand to benefit significantly from this evolution. The computational demands of autonomous agents – including increased data generation, processing requirements, and storage needs – may accelerate cloud adoption across industries. This trend presents opportunities throughout the technology value chain, from foundational infrastructure to specialized software solutions. Market Dynamics and Growth Projections Recent industry surveys indicate strong momentum for agentic AI adoption: Current projections estimate the agentic AI market reaching 47 billion by 2030 Infrastructure Implications and Emerging Opportunities The rise of autonomous AI systems is driving several structural changes in technology markets: Industry Adoption and Commercialization Leading technology providers have moved aggressively to capitalize on this trend: These developments suggest agentic AI is already reshaping enterprise software economics while demonstrating strong market acceptance despite premium pricing. Strategic Implications Agentic AI represents more than technological evolution – it signals a fundamental shift in how enterprises leverage artificial intelligence. By automating complex workflows and decision-making processes, these systems offer: As the technology matures, agentic AI appears poised to catalyze the next phase of cloud computing growth while creating new opportunities across the technology ecosystem. For enterprises and investors alike, understanding and positioning for this transition may prove critical in the coming years. Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 20, 2025in Agentic AI, Artificial Intelligence, Cloud Computing, Data, Enterprise, Generative AI, Salesforce, Technology
Data Data Data
19Mar

Data Lake vs. Data Warehouse: Understanding the Differences and Use Cases

Organizations today manage vast amounts of data, and how they store and process that data plays a critical role in business intelligence. Data lakes and data warehouses represent two distinct approaches to large-scale data storage, each with unique strengths. While they are often compared, they are not mutually exclusive—when used strategically, they complement each other to provide powerful insights. This guide explores the key differences between data lakes and data warehouses, their advantages, and when to use each. What is a Data Lake? A data lake is a centralized repository that stores vast amounts of raw data in its native format until needed. Unlike structured databases, data lakes use a flat architecture, meaning the data remains unprocessed and unstructured, retaining its original form. Key Features of Data Lakes: Challenges of Data Lakes: What is a Data Warehouse? A data warehouse is a structured repository optimized for analysis and business intelligence (BI). Unlike data lakes, which store raw data, data warehouses transform, clean, and organize data into a structured format for easy querying and reporting. Key Features of Data Warehouses: Challenges of Data Warehouses: Data Lake vs. Data Warehouse: Key Differences Feature Data Lake Data Warehouse Data Type Structured, semi-structured, and unstructured Primarily structured data Storage Format Raw, native format Processed and organized Use Case Big data, AI/ML analytics, real-time insights Business intelligence, reporting, transactions Cost Lower (scalable, less processing needed) Higher (due to transformation and storage costs) Flexibility High—schema-on-read Low—schema-on-write Ease of Use Requires data engineers and scientists Business analysts can use directly Security Less secure, requires governance More secure, with access control Choosing Between a Data Lake and Data Warehouse The best choice depends on the business objectives and data needs: Many organizations use both—storing raw data in a lake and processing refined data in a warehouse. For example, a company might: By integrating both storage solutions, businesses can maximize efficiency, reduce costs, and enable better decision-making. Conclusion Rather than viewing data lakes and data warehouses as competing technologies, organizations should recognize their complementary roles. While data warehouses provide structured, high-performance analytics, data lakes offer the flexibility needed for big data storage and ai-driven insights. The key to success is balancing both solutions to meet current and future data needs—ensuring agility, cost efficiency, and scalability in a rapidly evolving digital world. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 19, 2025in Salesforce
Salesforce Data Cloud Hits $900M in Revenue
18Mar

The Future of Real-Time Customer Intelligence

Salesforce Data Cloud Today: The Future of Real-Time Customer Intelligence Imagine a CRM That Knows Your Customers Better Than You Do The future of real-time customer intelligence is here now. What if your CRM could:✔️ Track every customer interaction in real time—purchases, social media activity, support tickets✔️ Predict their next move before they make it✔️ Automatically trigger hyper-personalized marketing, sales, and service actions that deliver incredible experiences That’s Salesforce Data Cloud (formerly known as Salesforce Genie)—an AI-powered Customer Data Platform (CDP) that turns raw data into real-time customer intelligence. Why Data Cloud is The Future of Real-Time Customer Intelligence Businesses today are drowning in data but starving for insights. Traditional CRMs rely on outdated, siloed information—leading to missed opportunities and generic customer experiences. Salesforce Data Cloud solves this by:🔹 Unifying data from every source (CRM, eCommerce, IoT, social media, third-party apps)🔹 Resolving duplicates into a single, dynamic customer profile🔸 Predicting behavior with Einstein AI to automate next-best actions🔺 Acting in real time—no more batch processing delays Example: Starbucks-Level Personalization (Without the Big Data Team) Starbucks uses a CDP to track your orders, app usage, and location to send personalized offers when you’re near a store.With Data Cloud, any business—big or small—can do the same. Generic communication is so 2020. Get with the times with Salesforce Data Cloud! How Salesforce Data Cloud Works (2025 Edition) 1. Data Ingestion: Bring Every Customer Signal Together Data Cloud connects:✔️ Salesforce records (Leads, Cases, Opportunities)✔️ External platforms (Shopify, Google Analytics, Meta Ads)✔️ IoT & live streams (smart devices, chatbots, in-store sensors) Example: A retailer tracks online purchases, in-store visits, and support chats—all in one profile. 2. Identity Resolution: No More Duplicate or Messy Data Ever had “John Smith” in your system five times? Data Cloud’s AI:✔️ Merges duplicates into one accurate profile✔️ Unifies all interactions (website visits, emails, purchases) 3. Real-Time Segmentation: Instant Customer Groups Forget manual reports—Data Cloud auto-creates segments like:🎯 “High-value customers who haven’t bought in 30 days”🎯 “Mobile app users at risk of churning” Example: A travel agent spots VIP clients searching for luxury trips and sends a personalized offer within seconds. 4. AI-Powered Actions: The Brain Behind the Scenes Einstein AI analyzes data and recommends:📞 Sales: “Call this lead now—90% chance to convert!”✉️ Marketing: “Send a discount—they’re price-sensitive.”🛠️ Service: “Their device is malfunctioning—proactively offer help.” Imagine the power at your fingertips with a CDP that intuitively advises next best actions with data-driven insights! Real-World Use Cases (2025 Success Stories) 1. Hyper-Personalized Retail Experiences ❌ Problem: A faurniture brand’s online & offline data were siloed, leading to generic promotions.✅ Solution: Data Cloud unifies: 2. Smarter B2B Sales Engagement ❌ Problem: A SaaS company lost deals because reps didn’t know the best time to follow up.✅ Solution: Data Cloud tracks: 3. Predictive Customer Service (Banking & Healthcare) ❌ Problem: Customers only reported issues when it was too late.✅ Solution: Data Cloud detects:🏦 Banking: “Unusual login attempt → Freeze account & text customer”🏥 Healthcare: “Missed prescription refill → Send automated reminder”📈 Result: 50% fewer escalations Why Old-School CRM Can’t Compete Traditional CRM Salesforce Data Cloud Static, siloed data Real-time unified profiles Manual segmentation AI-driven auto-segmentation Batch processing Instant triggers & actions Generic experiences Hyper-personalized engagement Think of it like upgrading from a flip phone to an AI assistant. How to Get Started in 2025 1️⃣ Check Compatibility (Available in Unlimited, Performance, Enterprise+ editions)2️⃣ Connect Key Data Sources (Start with Marketing Cloud, eCommerce platforms)3️⃣ Define Priority Segments (e.g., repeat buyers, at-risk customers)4️⃣ Automate Actions (Use Salesforce Flow + Einstein AI) 💡 Pro Tip: Pilot with one department (e.g., marketing) before scaling. The Future of Data Cloud (Beyond 2025) 🔮 Voice & AR Integration – Customers ask a voice assistant for help, and Data Cloud instantly pulls their full history.🔒 Blockchain-Powered Security – Decentralized identity verification to prevent fraud.🤖 AI-Generated Content – Einstein crafts personalized emails, ads, and product recs dynamically. Is Salesforce Data Cloud Worth It? ✅ For Marketers: 1:1 personalization at scale✅ For Sales Teams: Close deals faster with AI insights✅ For Service Teams: Solve issues before customers complain The future of CRM is real-time, AI-driven, and frictionless.Are you still relying on static data? Contact Tectonic to upgrade! Like Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 18, 2025in Data, Enterprise, Google, Google Analytics, Salesforce, Salesforce Data Cloud, Salesforce Flow
Salesforce Sales Engagement for Nonprofits
17Mar

Salesforce Sales Engagement for Nonprofits

Supercharge Your Nonprofit’s Donor Outreach with Salesforce Sales Engagement It’s time for the annual donor campaign. The fundraising team is juggling hundreds—if not thousands—of emails, phone calls, and follow-ups. The budget depends on surpassing last year’s donations, but with limited staff and time, reaching every potential donor feels impossible. The executive director asks, “How can we maximize donor engagement without increasing headcount—or at least focus our resources on the most likely givers?” Sound familiar? Every nonprofit faces the challenge of doing more with less. Fortunately, Salesforce offers a solution to keep your team organized, on task, and working smarter: Salesforce Sales Engagement. What Is Salesforce Sales Engagement? Salesforce Sales Engagement acts as a high-powered assistant for fundraising, membership, or program teams. This productivity hub, embedded within Salesforce, streamlines daily activities through automation, organization, and AI-powered insights. Key benefits include:✅ Cadences & Work Queues – Ensure no email, call, or task slips through the cracks.✅ Centralized Outreach – Keep all donor interactions in one place for seamless engagement.✅ AI-Driven Optimization – Analyze performance and refine strategies based on data. Previously known as High-Velocity Sales, Sales Engagement accelerates development cycles and scales outreach efforts effortlessly. By prioritizing critical tasks and automating others, your team can focus on building meaningful relationships and securing commitments faster. Engagement Cadences: Your Fundraising Playbook in Action Cadences serve as step-by-step roadmaps, guiding teams on how and when to engage with donors, members, or program participants. Whether you’re running a donor drive, promoting event registrations, or managing renewals, cadences ensure consistency and efficiency. Two Types of Cadences: 1️⃣ Standard Cadences – A structured sequence of touchpoints (emails, calls, LinkedIn messages) over time, such as a 30-day donor onboarding journey.2️⃣ Quick Cadences – A single, repeatable action, like automatically sending a thank-you email after a donation. With Cadence Builder, customizing workflows for different donor segments is fast and easy. Actions dynamically adjust based on engagement—so if a donor opens an email, they might receive a follow-up call; if they don’t, a reminder email is sent instead. Best of all, your team doesn’t have to track or remember each step—Sales Engagement assigns tasks automatically to individual work queues, ensuring nothing gets missed. Data-Driven Decision-Making with Built-In Analytics To improve outreach, you need to measure it. Sales Engagement provides powerful dashboards and reports to evaluate performance and optimize your approach. ✅ Track email open rates, call response rates, and donor engagement trends.✅ Identify successful messaging and refine underperforming campaigns.✅ Tie engagement metrics to fundraising goals to measure real impact. Unlike basic email tracking, Sales Engagement helps nonprofits connect data-driven insights with mission outcomes—empowering smarter decision-making without complex process changes. Already Using Salesforce Flows for Outreach? If your nonprofit relies on Salesforce Flow for outreach, you may wonder if Sales Engagement is necessary. The answer? Yes—if you want to do more with less effort. While flows are great for automation, Sales Engagement goes further with built-in call scripts, AI-powered task prioritization, and adaptable cadences. It offers a more intuitive, flexible approach to donor engagement, reducing manual work and boosting efficiency. Ready to Transform Your Fundraising Strategy? Salesforce Sales Engagement isn’t just for corporations—it’s a game-changer for nonprofits, helping teams increase donations, memberships, and event participation with less effort and greater impact. Are you ready to work smarter, engage better, and raise more? Let’s get started. Contact Tectonic today. Like1 Related Posts Who is Salesforce? Who is Salesforce? Here is their story in their own words. From our inception, we’ve proudly embraced the identity of Read more Salesforce Marketing Cloud Transactional Emails Salesforce Marketing Cloud Transactional Emails are immediate, automated, non-promotional messages crucial to business operations and customer satisfaction, such as order Read more Salesforce Unites Einstein Analytics with Financial CRM Salesforce has unveiled a comprehensive analytics solution tailored for wealth managers, home office professionals, and retail bankers, merging its Financial Read more AI-Driven Propensity Scores AI plays a crucial role in propensity score estimation as it can discern underlying patterns between treatments and confounding variables Read more

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March 17, 2025in Data, Salesforce, Salesforce Flow
gettectonic.com